An Innovative Scheme to Make an Initial Guess for Iterative Optimization Methods to Calibrate Material Parameters of Strain-Hardening Elastoplastic Models

Author(s)

Sanei, Manouchehr ^[1] ; Devloo, Philippe R. B. ^[2] ; Forti, Tiago L. D. ^[3] ; Duran, Omar ^[4] ; Santos, Erick S. R. ^[5]

Affiliation

^[1] Univ Estadual Campinas, Petr Engn Div, Mech Engn Dept FEM, Campinas, SP - Brazil

^[2] Univ Estadual Campinas, Civil Engn Dept FEC, Campinas, SP - Brazil

^[3] Simworx Engn Res & Dev, Campinas, SP - Brazil

^[4] Univ Paris Est, Ctr Enseignement & Rech Math & Calcul Sci, CERMICS ENPC, Paris - France

^[5] Petrobras SA, Res & Dev Ctr Cenpes, Rio De Janeiro, RJ - Brazil

• Document type: Journal article
• Source: ROCK MECHANICS AND ROCK ENGINEERING; v. 55, n. 1 OCT 2021.
• Web of Science Citations: 0

Abstract

Optimization can apply in almost every branch of science and technology. In particular, a gradient-based iterative method is a mathematical optimization procedure that can be used to make decisions. The gradient-based optimization method can only find a local minimum of the objective function if the algorithm starts with the appropriate initial data. The ambition of this article is to develop a new scheme to make an initial guess for iterative optimization methods to calibrate accurately the material parameters of strain-hardening elastoplastic constitutive models based on the test data. The elastoplastic models are Drucker-Prager and modified Cam-Clay, and the data obtained from triaxial, oedometric, and hydrostatic tests. The validity of proposed material parameters is evaluated using a home-made finite-element simulator. The results emphasize the ability of the proposed procedure to accurately calibrate material parameters. (AU)

• FAPESP's process: 17/15736-3 - Engineering Research Centre in Reservoir and Production Management
• Grantee: Denis José Schiozer
• Support Opportunities: Research Grants - Research Centers in Engineering Program